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oa Improving productivity and increasing Qatar reserves
- Publisher: Hamad bin Khalifa University Press (HBKU Press)
- Source: Qatar Foundation Annual Research Forum Proceedings, Qatar Foundation Annual Research Forum Volume 2010 Issue 1, Dec 2010, Volume 2010, EEO7
Abstract
At Texas A&M University at Qatar, the faculty, research staff, and students of the Petroleum Engineering Program are currently involved in and also planning for several research projects with four main objectives: improving productivity in Qatar's oil and gas fields; increasing the petroleum reserves of Qatar; developing a strong base of Qatari professionals; and preserving the environment.
One of our major projects is directed at enhancing the productivity of gas-condensate reservoirs which are commonly reduced due to condensate blocking. Our research team is tackling the problem on various fronts including a comprehensive experimental study on the wettability changes of rocks that can enhance liquid mobility and gas productivity; a simulation study to identify the critical parameters that need to be considered when trying to optimize well productivity; and a fundamental study that is targeting analytical modeling of multi-phase flow and the stability of various states of wettability at reservoir conditions. Funding for the various aspects of this work is supported by the Qatar National Research Fund's National Priorities Research Program (NPRP), RasGas, and Schlumberger.
Another active research area related to productivity enhancement deals with acid stimulation in carbonate reservoirs, which applies to almost every well in Qatar. Part of the work is aimed at enhancing the recovery of spent acid to speed the clean up process and improve gas productivity after stimulation. Another part deals with the development of an acid-jetting process as an improved and more effective stimulation process. More work is in the initial stages that targets optimizing the stimulation treatments in Qatar.
We are also actively working on developing models using artificial intelligence techniques to optimize applications of horizontal wells in gas condensate reservoirs with uncertain geological properties.
Our work on CO2 addresses two objectives: carbon sequestration and CO2 injection for improved oil recovery. We are conducting experimental, modeling, and simulation work to achieve these objectives.